Harvard and Google team up to made AI to predicts Earthquake aftershocks

Over the past few years, Earthquake researchers were trying to develop such technology which could predict aftershocks of the earthquake. Researchers of Google and Harvard can now accurately predict that when aftershocks will going to happen the time as well as the location of it. All of the predictions carried through Artificial intelligence (AI).

This week a paper published in the journal Nature in which the researchers talk about how deep learning can predict aftershocks location more accurately than the previous methods. For this, Researchers tested a neural network to look for the patterns of more than 131,000 Earthquakes present in the database and locations of the following aftershocks. Scientists can say that the deep learning is more reliable than the existing model, known as “Coulomb failure stress change.”

Brendan Meade, a professor of Earth and planetary sciences at Harvard who helped author the paper, told ScienceDaily that the results were amazing, “There are three things you want to know about earthquakes,” said Meade. “When they are going to occur, how big they’re going to be and where they’re going to be. Prior to this work, we had empirical laws for when they would occur and how big they were going to be, and now we’re working the third leg, where they might occur.”

They use a scale of accuracy from 0 to 10 in which 1 shows a perfectly accurate model and 0.5 model is like may or may not happen, the Coulomb model scored 0.583, whereas the new AI system hit 0.849. The artificial intelligence is a fancy pattern incorporated with a lot of data and in which algorithm finds the underlying pattern of aftershocks and location.

AI is extremely very helpful in this domain and especially in seismology where it is sometimes difficult to see connections as seismic activities control too many variables. Despite Google and Harvard collaboration over this research, the AI model only predicts the aftershocks that cause some permanent changes to the ground, but subsequent Earthquakes cause rumbling in the ground. This existing model too very slow to work on the real-time and yet can’t warn us earlier about the earthquakes. Though, researchers are still working to further enhance this model.